Single Tower Crane Allocation Using Ant Colony Optimization

Tower crane is one of the most versatile construction equipment that is needed in major projects. The determination of the location of the tower crane requires special consideration to its proximity to different facilities on site to optimize its performance. Several studies have been conducted on the optimization of single tower crane allocation using different techniques. The objective of this optimization problem is to minimize the total travel time used by the crane to deliver materials from supply to demand points. Mathematical and evolutionary algorithms (EAs) have been used in solving this problem. The algorithms used differ in their computational abilities, complexity, and performance. However, none of these models considered the application of Ant Colony Optimization (ACO) although it has been proved to be one of the most powerful swarm-based algorithms used for solving combinatorial optimization problems. This paper: 1) presents the modeling and application of ACO in solving the single tower crane allocation problem; 2) shows the performance of ACO in comparison to other techniques used in the literature to solve this problem, 3) highlights some of the discrepancies identified in previous models, which make them confusing to the readers. The main contribution of this paper lies in providing the illustration needed for modeling and solving single tower crane allocation problem using ACO. This should prove very useful in solving large problems where mathematical techniques cannot be used.